Lessons from Hollywood films on how to implement People Analytics

My wife and I go to the movies a lot. Well, at least we used to. 

Several years ago we became parents, so movie night out became movie night at home, but it was okay because you can stream just about anything. A couple years later, however, we decided to have another child. So movie night at home pretty much went away altogether and we entered a cinematic black hole. 

But that's also okay, because if you've watched a lot of movies, you know that there's not much original that comes out these days. Characters and plots may be different, but the underlying storylines repeat themselves. 

For example, think of that movie about an ice hockey player-turned-coach who took a group of all-American, undisciplined kids and coached them to play like they never played before, turning them into a team that believed they could achieve the unachievable, who ultimately defeats the more favored opponent.

So you might have surmised that I was talking about Miracle, the story of the 1980 men's US Olympic hockey team. I'll forgive you for being wrong; I was actually talking about the Mighty Ducks. But you can see my point: the details are different, but they're essentially the same story!

Now for a second let's think about a different variation of that story. Think about a movie about a group of talented young players who don’t come together under a strong coach, but still end up winning in the end. Can you think of one? Well it's a trick question: that movie was never made. It's sitting in a pile of screenplays on some producer’s desk, because that story rarely exists in real life. 

How does this matter to us in people analytics? The lesson is that successful people analytics implementations don't happen by themselves. They require committed leadership, teamwork, and discipline.  

So I'd like to share a few more lessons from Hollywood films that I think have a strong bearing on how we can successfully implement people analytics.

Navy SEALs

In Navy SEALs, Charlie Sheen stars as a headstrong Navy special operator. This in itself was a bit of a narrative trope, because it's so different different from what real military special operators are like. Most tend to be very disciplined and deliberate. So this bit of wisdom actually doesn’t come from the movie Navy SEALs (I just couldn’t refrain from making a Charlie Sheen reference), but rather from the real Navy SEALs.

The idea is that “Slow is smooth; smooth is fast.” What does that mean? In real life, SEALs don’t rush recklessly into a fight. They are methodical and calculated. We need to be the same in how we implement people analytics. You don't want to overwhelm people and ultimately hurt adoption, or bite off more than you can chew and fail to deliver. The lesson is don't try to do too much too fast. Being slow and intentional avoids creating other problems that slow you down more. 

Jerry Maguire

There are a ton of memorable lines from Tom Cruise's 1996 film Jerry Maguire, but I’ll focus on just one (and probably the most quoted). Early on, Jerry is trying to retain his last paying client who puts his commitment to the test and makes Jerry shout in front of the whole office, “Show me the money!” 

Now you're not necessarily going to have anybody shouting this at you, but I guarantee there's somebody thinking it, and that person generally has a “C” in their title: CEO, CFO, CHRO... At some point they’re going to want to see the financial value that people analytics brings. If you aren’t able to show them, within a reasonable amount of time, you are going to get shut down. 

To show them the money, you need to have a value plan. This involves a long-range plan that looks several years ahead, a short-range plan that translates into specific projects, and project plans to ensure they’re each successful. The lesson is to build a roadmap to demonstrate business value early. If there isn't an obvious opportunity, create one. 

Rush Hour

Rush Hour was billed as the fastest hands in the East meeting in the biggest mouth in the West. In one particularly memorable scene, Chris Tucker, in a fit of frustration over poor communication, asks Jackie Chan, "Do you understand the words that are coming out of my mouth?!” 

Well in people analytics, words matter too. It’s not unheard of for people to be using the same words, but speaking about entirely differently things. Here's a quick experiment: ask 10 co-workers, separately, who in your company is a “Senior Leader.” You’ll probably get 10 different answers. 

To be on the same page when communicating, it helps to have a data dictionary; something to integrate a common language into all communications. Appreciate the need for the organization to have a shared understanding of people data. If you don't, you will always have challenges. 

The Karate Kid

Our next movie is The Karate Kid. You may be asking, what can Mr. Miyagi teach us about people analytics? And if you are, you're asking the wrong question. The right question, is what can't Mr. Miyagi teach us about people analytics. And the answer is nothing. There are no less than three dozen lessons we can learn from The Karate Kid, but I’ll focus on one exemplified by the timeless line, "Wax on, wax off."

Mr. Miyagi had a variety of teaching methods, during some of which Daniel didn't even realize he was even learning. It's probably worth rethinking how you go about upskilling HR team members and business leaders. Create a host of various enablement methods and resources: things that help people learn in different ways at different times.  

The lesson is you need to create varied learning opportunities. Mentor, coach, and find teachable moments. It won't make sense to some people. That's okay. 

Minority Report

Next up is Minority Report, a Sci-Fi Spielberg flick. In the not too distant future, Tom Cruise leads a "precognition crime" unit that can predict murders before they happen. In one scene he’s defending his program to an auditor and says “There's nothing wrong with the system, it is perfect.” ...And then he subsequently ends up getting framed for murder by his own system.  

With the increase in computing power, and recent developments in artificial intelligence and machine learning, we’re going to continue to have more predictive and other AI capabilities at our disposal in people analytics. They pose great opportunities, but also great risks.

You need to understand both the capabilities and limitations of the technology (and then probably get your lawyers comfortable).

School House Rock

Our penultimate feature is School House Rock. And yes, I know, that's not technically a movie, but they always had a great lesson. In a very memorable one, a Bill sitting on Capitol Hill sings “I know I’ll be a law someday.”

Why is this important? The rate of AI/ML technology development, at least in the near term, is going to vastly outpace the regulatory efforts, which creates a whole host of issues to think about. Expert testimony to Congress recently recommended the creation of AI-specific regulatory bodies. The intention behind this may be good, but these algorithms can be complex and hard to understand, which makes effective regulation hard at the beginning. 

Imagine having Congressional staffers who don't understand AI or machine learning - and maybe not even HR, for that matter - who are writing laws that regulate how we use predictive analytics. Now, not to get too political here, but we’ve all seen what happens when a government tries to take on a threat that it doesn't really understand and is ill-equipped to deal with... 

Yeah, that's what happens. Aliens blow-up Washington. So the lesson is really, really get your lawyers comfortable. Even better, engage your government affairs to get involved and help shape any legislation in the right ways.

The Matrix

On to our finale. The Matrix, a Sci-Fi classic. After getting a “fighting program” digitally uploaded directly into his brain, Keanu Reeves memorably says: “I know Kung Fu.” Personally, I would love to be able to plug something in the back of everybody's head to get them to instantaneously understand people analytics (we can all dream, right?). But this is the real world, not sci-fi.  

Understand that things won’t happen overnight. Think about how to provide multimodal continuous learning so you can engage with people on different platforms at different times. Stay consistent with your effort, but not necessarily with your approach. Needs vary and evolve, so be prepared to adapt over time and to different individuals.  

The lesson is to meet people where they're at. Be patient. Building the mindset and the skillset for people analytics takes time. There are no shortcuts.